Scientific Research

Applied Statistics

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Microsoft Office



Data Scientist

Research Branch, Ministry of Social Development & Poverty Reduction, Province of British Columbia

Apr 2020 – Present Victoria, BC, Canada

  • Statistical modelling, hypothesis testing, and machine learning with R & SAS.
  • Studying the recent history of government service utilization in the Downtown Eastside neighbourhood of Vancouver to characterize (mental) health, socioeconomic, and demographic relationships with poverty and homelessness. You can learn more about this data innovation program project here.
  • In partnership with the BC Centre for Disease Control, I am leading a team of 4 researchers seeking to use unsupervised machine learning and statistical models to identify determinants of overdose risk among British Columbians struggling with opioid addiction.
  • Advising executives on the use of quantitative methods to address strategic knowledge gaps.
  • Developing an R package, “elucidate”, to make data analysis easier for scientific researchers.
  • Querying, modifying, and constructing relational databases using SQL and Git Bash.
  • Cleaning, transforming, and processing high dimensional data (millions of rows) to facilitate reproducible analysis.

Data Science Fellow

Office of the Chief Information Officer, Ministry of Citizen’s Services, Province of British Columbia

May 2019 – Apr 2020 Victoria, BC, Canada

  • Applied time-series regression models to simultaneously evaluate the effects of multiple social assistance policies and economic recessions on social assistance program utilization and estimate the costs of service delivery.
  • Designed and began to conduct a team research project examining the government service utilization history of Vancouver.
  • Created an R package, “elucidate”, to make exploratory data analysis easier for researchers.
  • Queried, modified, and constructed relational database tables using SQL and Git Bash.
  • Cleaned, transformed, and processed high dimensional data (millions of rows) to facilitate reproducible analysis in secure analytics environments.

Postdoctoral Fellow in Neuroscience

Division of Medical Sciences, University of Victoria

Oct 2018 – Apr 2019 Victoria, BC, Canada

  • Statistical modelling, hypothesis testing, and machine learning with R.
  • Cleaning, transforming, and processing high dimensional health data to facilitate reproducible analysis.
  • Discovering health-related patterns and predictors in experimental and epidemiological data.
  • Uncovered novel therapeutic targets for post-concussion treatment via differential expression analysis of proteomics data.
  • Leveraged multiple correspondence analysis and clustering to identify disease comorbidity patterns using questionnaire data from over 50,000 participants in the Canadian Longitudinal Study on Aging (CLSA;
  • Predicted concussion status with over 95% test accuracy based on demographic information, clinical history, and cognitive evaluations from hundreds of patients with a decision tree and used permutation techniques to characterize concussion-related behavioural impairments many months after a traumatic brain injury.


Doctoral Researcher

Department of Psychology, Neuroscience, & Behaviour, McMaster University

Sep 2013 – Sep 2018 Hamilton, ON, Canada

  • Designed and oversaw multiple projects investigating the effects of lifestyle modifications on learning, memory, anxiety, and mood in animal models of depression and Alzheimer’s disease.
  • Employed domain knowledge, unsupervised learning (hierarchical clustering and principal component analysis), and predictive modeling (logistic and linear regression) with R.
  • Identified dietary patterns conducive to healthy brain aging using data from 30,000 Canadians.
  • Established and coordinated a collaborative research program between 5 different laboratories across McMaster University and the University of Toronto.
  • Used random forest models to predict depression with 87% test accuracy based on lifestyle patterns and cognitive data from over 30,000 Canadians.
  • Coded, manipulated, visualized, and analysed various data types using R and SPSS.
  • Communicated research findings to stakeholders and senior decision-makers in organizational meetings, peer-reviewed publications, and at 10 conferences (national and international).

Teaching Assistant

Department of Psychology, Neuroscience, & Behaviour, McMaster University

Sep 2013 – Apr 2018 Hamilton, ON, Canada

  • Designed and graded testing material including written assignments, tests/exams, and oral presentations.
  • Lectured in cognitive neuroscience courses on several occasions.
  • Mentored undergraduate students in research design, ethics, data collection, data analysis and science communication.
  • Supervised numerous student-run community outreach projects.
  • Taught students how to use statistical software.
  • Reviewed tests and monitored/updated electronic learning platforms.

Undergraduate Research Assistant

Department of Psychology, University of Winnipeg

Sep 2008 – May 2013 Winnipeg, MB, Canada

  • Completed multiple pharmacological studies in models of addiction and amnesia.
  • Assisted with data collection, management, analysis (using SPSS), and interpretation.
  • Communicated analytical results at 2 conferences and in written reports.

Recent Posts

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1 TL;DR 2 Introduction 3 Setup 4 ggplot2 basics 5 aesthetic customization 5.1 titles/labels 5.2 fill 5.3 colour/color 5.4 reordering factors 5.5 colour palettes 5.6 colourblind-friendly palettes 5.7 size 5.8 shape 5.9 linetype 5.10 alpha (transparency/opacity) 5.11 jittering to reduce overplotting 5.12 coordinates 5.12.1 coord_flip() 5.12.2 coord_cartesian() 5.13 guides (legends) 5.14 x & y axis modifications 5.14.1 scale_x_continuous()/scale_y_continuous() 5.14.2 scale_x_discrete()/scale_y_discrete() 5.

1 TL;DR 2 Introduction 3 Installation & Setup 4 Interrogating Data 4.1 checking for row copies() and dupes() 4.2 count()-ing unique values 4.3 describe()-ing missingness & extreme values 5 Descriptives 5.1 describe() a vector with summary statistics 5.2 grouped descriptions 5.3 describe_all() columns in a data frame 5.4 confidence intervals 6 To see, look 6.1 Anscombe’s lesson: numeric descriptions can be misleading 6.2 plot_*-ting data with elucidate 6.

1 TL;DR 2 Introduction 2.1 load packages 3 date/time basics 4 which day is it? 5 reading dates 6 time zones 7 month names 8 extracting datetime components 9 days in a month 10 custom date formats 11 date calculations 11.1 correcting excel date-to-numeric conversions 12 planning a behavioural neuroscience experiment 12.1 turning the planning script into a function 13 Navigation 14 Notes 1 TL;DR Dates/times are the last type of data you’ll probably work with on a fairly regular basis.

1 TL;DR 2 Introduction 2.1 load packages 2.2 import data 3 Factor basics 4 factors and data visualization 5 factors and modelling 6 Navigation 7 Notes 1 TL;DR Factors are one of the two remaining types of data you’ll encounter on a fairly regular basis. This post will show you how to use the forcats tidyverse package in R so you’ll know how to handle factors when you encounter them.


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(2019). Modulation of synaptic plasticity by exercise. International Review of Neurobiology, 147, 295-322..



Ontario Graduate Scholarship

Host Institution: McMaster University

Supervisor: Dr. Sue Becker

Amount: $15,000

Canada Graduate Scholarship - Doctoral Program

Host Institution: McMaster University

Supervisor: Dr. Sue Becker

Amount: $35,000/year

See certificate

Canada Graduate Scholarship - Master’s Program

Host Institution: McMaster University

Supervisor: Dr. Sue Becker

Amount: $17,500

See certificate

Certificate of Academic Excellence – Honours Thesis

See certificate

Undergraduate Student Research Award

Host Institution: University of Winnipeg

Supervisor: Dr. Harinder Aujla

Amount: $4,500 from NSERC + $2,500 from Dr. Aujla

See certificate

Recent & Upcoming Talks

Abstract In 2019, there were there were 24,166 overdose ambulance calls (~66/day) in BC, and in the Vancouver Coastal Health Region 39% …